In the last few years, hundreds of peer-reviewed scientific papers have been published linking changes in solar activity to Earth’s climate (2016, 2017, 2018). The evidence for a robust Sun-Climate connection continues to accumulate in 2019.
When it comes to the Sun’s influence on climate, one conclusion is certain: there is no widespread scientific agreement as to how and to what extent solar activity and its related parameters (i.e., galactic cosmic rays, geomagnetic activity, solar wind flux) impact changes in the Earth’s temperature and precipitation.
The disagreement is so chasmic and the mechanisms are so poorly understood that scientists’ estimates of the influence of direct solar irradiance forcing between the 17th century and today can range between a negligible +0.1 W m-2 to a very robust +6 W m-2 (Egorova et al., 2018; Mazzarella and Scafetta, 2018).
“There is no consensus on the amplitude of the historical solar forcing. The estimated magnitude of the total solar irradiance difference between Maunder minimum and present time ranges from 0.1 to 6 W/m2 making uncertain the simulation of the past and future climate.” (Egorova et al., 2018)
“According to the IPCC (2013), solar forcing is extremely small and cannot induce the estimated 1.0–1.5 °C since the LIA. However, thesolar radiative forcing is quite uncertain because from 1700 to 2000 the proposed historical total solar irradiance reconstructions vary greatly from a minimum of 0.5 W/m2 to a maximum of about 6 W/m2 (cf..: Hoyt and Schatten 1993; Wang et al. 2005; Shapiro et al. 2011). Moreover, it is believed that the sun can influence the climate also via a magnetically induced cosmic ray flux modulation (e.g.: Kirkby 2007) or via heliospheric oscillation related to planetary resonances (e.g.: Scafetta 2013, 2014b; Scafetta et al. 2016, and others). Since solar and climate records correlate quite significantly throughout the Holocene (cf: Kerr 2001; Steinhilber et al. 2012; Scafetta 2012, 20104b), the results shown herein may be quite realistic, although the exact physical mechanisms linking astronomical forcings to climate change are still poorly understood.” (Mazzarella and Scafetta, 2018)
Thus far in 2019, 55 scientific papers have been located that link solar forcing to climate changes. This is an incomplete compilation and it is likely to swell to about ~100 papers by year’s end or upon further review.
Such a large volume of research devoted to finding connections between the Sun’s variability and its effect on the Earth’s climate system would seem to contradict the conclusion that there is widespread consensus that the Sun’s climate impact is negligible.
Below are the first 12 papers on the list. For the rest of the compilation, click here.
Scafetta and Willson, 2019 The consistent downward trending of the PMOD TSI composite is negatively correlated with the global mean temperature anomaly during 1980–2000. This has been viewed with favor by those supporting the CO2 anthropogenic global warming (CAGW) hypothesis since it would minimize TSI variation as a competitive climate change driver to CO2, the featured driver of the hypothesis during the period (cf.: [IPCC, 2013, Lockwood and Fröhlich, 2008]). .. Our summary conclusion is that the objective evidence produced by all of the independent TSI composites [3,5, 6, 9] agrees better with the cycle-by-cycle trending of the original ACRIM science team’s composite TSI that shows an increasing trend from 1980 to 2000 and a decreasing trend thereafter. The continuously downward trending of the PMOD composite and TSI proxy models is contraindicated. … PMOD’s modifications of the published ACRIM and ERB TSI records are questionable because they are based on conforming satellite observational data to proxy model predictions. … ACRIM shows a 0.46 W/m2 increase between 1986 and 1996 followed by a decrease of 0.30 W/m2 between 1996 and 2009. PMOD shows a continuous, increasing downward trend with a 1986 to 1996 decrease of 0.05 W/m2 followed by a decrease of 0.14 W/m2 between 1996 and 2009. The RMIB composite agrees qualitatively with the ACRIM trend by increasing between the 1986 and 1996 minima and decreasing slightly between 1996 and 2009. … ACRIM composite trending is well correlated with the record of global mean temperature anomaly over the entire range of satellite observations (1980–2018) [Scafetta. 2009]. The climate warming hiatus observed since 2000 is inconsistent with CO2 anthropogenic global warming (CAGW) climate models [Scafetta, 2013, Scafetta, 2017]. This points to a significant percentage of the observed 1980–2000 warming being driven by TSI variation [Scafetta, 2009, Willson, 2014, Scafetta. 2009]. A number of other studies have pointed out that climate change and TSI variability are strongly correlated throughout the Holocene including the recent decades (e.g., Scafetta, 2009, Scafetta and Willson, 2014, Scafetta, 2013, Kerr, 2001, Bond et al., 2001, Kirkby, 2007, Shaviv, 2008, Shapiro et al., 2011, Soon and Legates, 2013, Steinhilber et al., 2012, Soon et al., 2014). .. The global surface temperature of the Earth increased from 1970 to 2000 and remained nearly stable from 2000 and 2018. This pattern is not reproduced by CO2 AGW climate models but correlates with a TSI evolution with the trending characteristics of the ACRIM TSI composite as explained in Scafetta [6,12, 27] and Willson .
Pei et al., 2019 During the period of 0–10,000 yr BP, China’s temperature has closely followed the solar forcing. The correlation is as high as 0.800 (p < 0.01) for the EOF-based reconstruction. … Similar to the North Atlantic SST, AO also plays an important role in China’s temperature (Zuo et al., 2015). NAO and AO are both suggested to influence the climate in East Asia by modifying the strength and location of the 200 hPa jet stream (Yang et al., 2004). The AO record of Darby et al. (2012) is based on sea-ice drift, which has a high resolution of 10–100 years and shows a close connection with solar activities.
Jiao et al., 2019 Regional climate change is affected by large-scale climate-forcing factors, such as solar activity and atmospheric–oceanic variability (Fang et al., 2010; Linderholm et al., 2015; Rydval et al., 2017). On the one hand, based on the MTM analysis results, the temperature changes in the study area are mainly influenced by the solar activity via the mean minimum temperature within approximately 11-year periods (Li et al., 2006; Wang et al., 2015). The tree-ring chronology was developed by samples of Schrenk spruce collected from the National Nature Reserve of the Western Tianshan Mountains. The mean minimum temperature in the growing season is the main and stable limiting climate factor. Therefore, the mean minimum temperature series in the growing season during 1680–2012 was reconstructed based on the STD chronology. In the past 333 years, the mean minimum temperature has roughly experienced three relatively cold periods and relatively warm stages (relatively cold periods: 1680–1707, 1802–1911 and 1935–1997; relatively warm periods: 1708–1801, 1912–1934 and 1998–2012). By analyzing similar trends in regional temperature changes in our reconstruction series with drought events, large volcanic eruptions and other reconstruction series around the study regions in Xinjiang and even large-scale regions, we found that the mean minimum temperature of the reconstruction was accurate and reliant. Moreover, the mean minimum temperature was influenced by solar activity (sunspots) and large-scale atmospheric–oceanic fluctuations (NAO, WPO, ENSO, TBO) based on the MTM and spatial correlation analysis.